For Your Ears Only: Personalizing Spotify Home with Machine Learning

This post details the application of Spotify's ML-driven personalization systems to the Spotify Home screen. It highlights the scale challenges compared to other platforms and the transition from custom data libraries to a standardized ML infrastructure using TensorFlow Extended (TFE) and Kubeflow. Key technical details include the use of a multi-armed bandit framework for balancing exploitation and exploration, counterfactual training, and the benefits of TFDV for data pipeline bug detection and consistency checks. The post emphasizes the shift towards engineer productivity and innovation by focusing on a 'Paved Road' approach to ML infrastructure.